Surveillance footage for activity analysis in complicated scenes

This dataset, the SAIVT-Campus Database is an abnormal event detection database captured at the Queensland University of Technology, Australia. It contains two video files from real world surveillance footage without any actors. Each video file is one hour in duration. The normal activities include pedestrians entering or exiting the building, entering or exiting a lecture theatre (yellow door), and going to the counter at the bottom right. The abnormal events are caused by a heavy rain outside, and include people running in from the rain, people walking towards the door to exit and turning back, wearing raincoats, loitering and standing near the door and overcrowded scenes. The rain happens only in the later part of the test dataset. As a result, we assume that the training dataset only contains the normal activities.

本数据集为SAIVT-Campus数据库（SAIVT-Campus Database），是采集自澳大利亚昆士兰科技大学（Queensland University of Technology）的异常事件检测数据库。其包含两段取自真实监控录像的视频文件，无任何人工参演人员，单段视频时长均为1小时。正常活动涵盖行人进出楼宇、进出报告厅（黄色门），以及前往右下角服务台的行为。异常事件由室外强降雨引发，具体表现为人们冒雨奔跑、走向出口门后折返、身着雨衣、在门附近徘徊驻足，以及场景出现人员过度拥挤的情况。降雨仅出现在测试数据集的后半段，因此我们假设训练数据集仅包含正常活动样本。